Martingales #
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A family of functions f : ι → Ω → E is a martingale with respect to a filtration ℱ if every
f i is integrable, f is adapted with respect to ℱ and for all i ≤ j,
μ[f j | ℱ i] =ᵐ[μ] f i. On the other hand, f : ι → Ω → E is said to be a supermartingale
with respect to the filtration ℱ if f i is integrable, f is adapted with resepct to ℱ
and for all i ≤ j, μ[f j | ℱ i] ≤ᵐ[μ] f i. Finally, f : ι → Ω → E is said to be a
submartingale with respect to the filtration ℱ if f i is integrable, f is adapted with
resepct to ℱ and for all i ≤ j, f i ≤ᵐ[μ] μ[f j | ℱ i].
The definitions of filtration and adapted can be found in probability.stopping.
Definitions #
measure_theory.martingale f ℱ μ:fis a martingale with respect to filtrationℱand measureμ.measure_theory.supermartingale f ℱ μ:fis a supermartingale with respect to filtrationℱand measureμ.measure_theory.submartingale f ℱ μ:fis a submartingale with respect to filtrationℱand measureμ.
Results #
measure_theory.martingale_condexp f ℱ μ: the sequenceλ i, μ[f | ℱ i, ℱ.le i])is a martingale with respect toℱandμ.
A family of functions f : ι → Ω → E is a martingale with respect to a filtration ℱ if f
is adapted with respect to ℱ and for all i ≤ j, μ[f j | ℱ i] =ᵐ[μ] f i.
Equations
- measure_theory.martingale f ℱ μ = (measure_theory.adapted ℱ f ∧ ∀ (i j : ι), i ≤ j → measure_theory.condexp (⇑ℱ i) μ (f j) =ᵐ[μ] f i)
A family of integrable functions f : ι → Ω → E is a supermartingale with respect to a
filtration ℱ if f is adapted with respect to ℱ and for all i ≤ j,
μ[f j | ℱ.le i] ≤ᵐ[μ] f i.
Equations
- measure_theory.supermartingale f ℱ μ = (measure_theory.adapted ℱ f ∧ (∀ (i j : ι), i ≤ j → measure_theory.condexp (⇑ℱ i) μ (f j) ≤ᵐ[μ] f i) ∧ ∀ (i : ι), measure_theory.integrable (f i) μ)
A family of integrable functions f : ι → Ω → E is a submartingale with respect to a
filtration ℱ if f is adapted with respect to ℱ and for all i ≤ j,
f i ≤ᵐ[μ] μ[f j | ℱ.le i].
Equations
- measure_theory.submartingale f ℱ μ = (measure_theory.adapted ℱ f ∧ (∀ (i j : ι), i ≤ j → f i ≤ᵐ[μ] measure_theory.condexp (⇑ℱ i) μ (f j)) ∧ ∀ (i : ι), measure_theory.integrable (f i) μ)
The converse of this lemma is measure_theory.submartingale_of_set_integral_le.
A predictable submartingale is a.e. greater equal than its initial state.
A predictable supermartingale is a.e. less equal than its initial state.
A predictable martingale is a.e. equal to its initial state.
Given a discrete submartingale f and a predictable process ξ (i.e. ξ (n + 1) is adapted)
the process defined by λ n, ∑ k in finset.range n, ξ (k + 1) * (f (k + 1) - f k) is also a
submartingale.